Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila

Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg

Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics from electron microscopy to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it was unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to mechanosensory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. These findings are consistent with a growing body of work in invertebrate and vertebrate species demonstrating the existence of specialized limb mechanosensory pathways for sensing external vibrations.

A competitive disinhibitory network for robust optic flow processing in Drosophila

Many animals navigate using optic flow, detecting rotational image velocity differences between their eyes to adjust direction. Forward locomotion produces strong symmetric translational optic flow that can mask these differences, yet the brain efficiently extracts these binocular asymmetries for course control. In Drosophila melanogaster, monocular horizontal system neurons facilitate detection of binocular asymmetries and contribute to steering. To understand these functions, we reconstructed horizontal system cells' central network using electron microscopy datasets, revealing convergent visual inputs, a recurrent inhibitory middle layer and a divergent output layer projecting to the ventral nerve cord and deeper brain regions. Two-photon imaging, GABA receptor manipulations and modeling, showed that lateral disinhibition reduces the output's translational sensitivity while enhancing its rotational selectivity. Unilateral manipulations confirmed the role of interneurons and descending outputs in steering. These findings establish competitive disinhibition as a key circuit mechanism for detecting rotational motion during translation, supporting navigation in dynamic environments.

Comparative connectomics of Drosophila descending and ascending neurons

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and an information bottleneck connecting the brain and the ventral nerve cord (an analogue of the spinal cord) and comprises diverse populations of descending neurons (DNs), ascending neurons (ANs) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Here, by integrating three separate electron microscopy (EM) datasets1-4, we provide a complete connectomic description of the ANs and DNs of the Drosophila female nervous system and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions are matched across hemispheres, datasets and sexes. Crucially, we also match 51% of DN cell types to light-level data5 defining specific driver lines, as well as classifying all ascending populations. We use these results to reveal the anatomical and circuit logic of neck connective neurons. We observe connected chains of DNs and ANs spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analyses of selected circuits for reproductive behaviours, including male courtship6 (DNa12; also known as aSP22) and song production7 (AN neurons from hemilineage 08B) and female ovipositor extrusion8 (DNp13). Our work provides EM-level circuit analyses that span the entire central nervous system of an adult animal.

Play-like behavior exhibited by the vinegar fly Drosophila melanogaster

Anecdotal accounts about animals repeatedly exposing themselves to sources of passive movement by engaging with swings, slides, or carousels are generally assumed to be "play." Criteria for play-like behavior require the activity to be (1) of no immediate relevance for survival; (2) voluntary, intentional, and rewarding; (3) non-ethotypical; (4) repeated, yet unstereotyped; and (5) free from stress.1,2 Play-like behavior following these rules is pervasive across the vertebrate subphylum2; recent studies in rats even identified and characterized the involved brain regions.3,4 In invertebrates, sparse reports have so far addressed either social play in parasitoid wasps or spiders,5,6 object play in bumblebees,7 or are anecdotal.1 Contrary to social play or object play, which are thought to train social interaction or muscle/motor skills, respectively, a convincing hypothesis of the adaptive value of voluntary passive movement play-like behavior is currently lacking in any organism. Like other animals, flies are highly sensitive to the direction of gravitational pull,8 hence such intentional passive motion could be sufficient to induce proprioceptive stimulation externally.9 Here, we identify voluntary spinning on a carousel as idiosyncratic play-like behavior in the vinegar fly Drosophila melanogaster: while some flies show spontaneous avoidance, others actively seek stimulation, engaging in repeated, prolonged visits to the carousel. We propose that animals voluntarily expose themselves to external forces, thus intentionally receiving exafferent stimulation. This deliberate, yet indirect, proprioceptive stimulation provides an efficient way to improve self-perception via internal model training and shaping multisensory integration. Importantly, this theoretical framework can now be tested empirically in flies. VIDEO ABSTRACT.

Single Objective Light Sheet Microscopy allows high-resolution in vivo brain imaging of Drosophila

In vivo imaging of dynamic sub-cellular brain structures in Drosophila melanogaster is key to understanding several phenomena in neuroscience. However, its implementation has been hindered by a trade-off between spatial resolution, speed, photobleaching, phototoxicity, and setup complexity required to access the specific target regions of the small brain of Drosophila . Here, we present a single objective light-sheet microscope, customized for in vivo imaging of adult flies and optimized for maximum resolution. With it, we imaged the axonal projections of small lateral ventral neurons (known as s-LNvs) in intact adult flies. We imaged the plasma membrane, mitochondria, and dense-core vesicles with high spatial resolution up to 370 nm, ten times lower photobleaching than confocal microscopy, lower invasiveness and complexity in sample mounting than alternative light-sheet technologies, and without relying on phototoxic pulsed infrared lasers. This unique set of features paves the way for new long-term, dynamic studies in the brains of living flies.

The neuroethology of ant navigation

Unlike any other group of animals, all ant species are social: individual ants share the food they gather with their nestmates and as a consequence they must repeatedly leave their nest to find food and then return home with it. These back-and-forth foraging trips have been studied for about a century and much of our growing understanding of the strategies underlying animal navigation has come from these studies. One important strategy that ants use to keep track of where they are on a foraging trip is 'path integration', in which they continuously update a 'home vector' that gives their estimated distance and direction from the nest. As path integration accumulates errors, it cannot be relied on to bring ants precisely home: such precision is accomplished by using views of the nest acquired before they start foraging. Further learning is scaffolded by home vectors or remembered food vectors, which guide a route and help in learning useful views experienced on the way. Many species rely on olfaction as well as vision for route guidance and the full details of their foraging paths have revealed how ants use a mix of innate and learnt multisensory cues. Wood ants, a species on which we focus in this review, take an oscillating path along a pheromone trail to sample odours, but acquire visual information only at the peaks and troughs of the oscillations. To provide a working model of the neural basis of the multimodal navigational strategies of ants, we outline the anatomy and functioning of major central brain areas and neural circuits - the central complex, mushroom bodies and lateral accessory lobes - that are involved in the coordination of navigational behaviour and the learning of visual and olfactory patterns. Because ant brains have not yet been well-studied, we rely on the work that has been done with other species - notably, Drosophila, silkworm moths and bees - to derive plausible neural circuitry that can deliver the ants' navigational strategies.

Theory of morphodynamic information processing: Linking sensing to behaviour

The traditional understanding of brain function has predominantly focused on chemical and electrical processes. However, new research in fruit fly (Drosophila) binocular vision reveals ultrafast photomechanical photoreceptor movements significantly enhance information processing, thereby impacting a fly's perception of its environment and behaviour. The coding advantages resulting from these mechanical processes suggest that similar physical motion-based coding strategies may affect neural communication ubiquitously. The theory of neural morphodynamics proposes that rapid biomechanical movements and microstructural changes at the level of neurons and synapses enhance the speed and efficiency of sensory information processing, intrinsic thoughts, and actions by regulating neural information in a phasic manner. We propose that morphodynamic information processing evolved to drive predictive coding, synchronising cognitive processes across neural networks to match the behavioural demands at hand effectively.

Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg

Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics from electron microscopy to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it was unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to mechanosensory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. These findings are consistent with a growing body of work in invertebrate and vertebrate species demonstrating the existence of specialized limb mechanosensory pathways for sensing external vibrations.

Fine-grained descending control of steering in walking Drosophila

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here, we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream of distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Our results suggest that a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from specific, coordinated modulations of low-level patterns.

Continuous integration of heading and goal directions guides steering

Navigating animals must integrate a diverse array of sensory cues into a single locomotor decision. Insects perform intricate navigational feats using a brain region termed the central complex in which an animal's heading direction is transformed through several layers of circuitry to elicit goal-directed locomotion. These transformations occur mostly in the fan-shaped body (FB), a major locus of multi-sensory integration in the central complex. Key aspects of these sensorimotor computations have been extensively characterized by functional studies, leveraging the genetic tools available in the fruit fly. However, our understanding of how neuronal activity in the FB dictates locomotor behaviors during navigation remains enigmatic. Here, we manipulate the activity of two key neuronal populations that input into the FB-the PFNa and PFNd neurons-used to encode the direction of two complex navigational cues: wind plumes and optic flow, respectively. We find that flies presented with unidirectional optic flow steer along curved walking trajectories, but silencing PFNd neurons abolishes this curvature. We next use optogenetic activation to introduce a fictive heading signal in the PFNs to establish the causal relationship between their activity and steering behavior. Our studies reveal that the central complex guides locomotion by summing the PFN-borne directional signals and shifting movement trajectories left or right accordingly. Based on these results, we propose a model of central complex-mediated locomotion wherein the fly achieves fine-grained control of sensory-guided steering by continuously integrating its heading and goal directions over time.

Divergent visual ecology of Drosophila species drives object-tracking strategies matched to landscape sparsity

Maintaining stable gaze while tracking moving objects is commonplace across animal taxa, yet how diverse ecological needs impact these processes is poorly understood. During flight, the fruit-eating fly Drosophila melanogaster maintains course by making smooth steering adjustments to fixate the image of the distant visual background on the retina, while executing body saccades to investigate nearby objects such as food sources. Cactophilic Drosophila mojavensis live where there is no canopy; rather, the flora forming visual "background" and "objects" are one and the same. We tested whether D. mojavensis have adapted their flight control strategies for a visually sparse landscape. We used a magnetic tether that allows free movement in the yaw axis. In response to a textured bar moving across a similarly textured stationary background, D. melanogaster fixates the background, thereby stabilizing gaze while integrating bar dynamics to trigger tracking saccades. By contrast, two mojavensis subspecies in the repleta subgroup and one species in the melanogaster subgroup steer to smoothly fixate the bar, seemingly ignoring the stationary surround. Desert flies execute frequent bar-tracking saccades, but theirs are triggered when rotational velocity lags the bar. Thus, D. melanogaster, which lives in visually cluttered cosmopolitan habitats, leverages the optical disparities between nearby objects and distant foliage for a hybrid control strategy: "ground-fixate, object-saccade." Flies in distant phylogenetic subgroups with similar visual ecology use a "fixate-and-saccade" strategy, which would be adaptive in a visually sparse environment where individual landscape features are both approached and used to maintain a straight course.

Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila

To navigate complex environments, walking animals must detect and overcome unexpected perturbations. One technical challenge when investigating adaptive locomotion is measuring behavioral responses to precise perturbations during naturalistic walking; another is that manipulating neural activity in sensorimotor circuits often reduces spontaneous locomotion. To overcome these obstacles, we introduce miniature treadmill systems for coercing locomotion and tracking 3D kinematics of walking Drosophila. By systematically comparing walking in three experimental setups, we show that flies compelled to walk on the linear treadmill have similar stepping kinematics to freely walking flies, while kinematics of tethered walking flies are subtly different. Genetically silencing mechanosensory neurons altered step kinematics of flies walking on the linear treadmill across all speeds. We also discovered that flies can maintain a forward heading on a split-belt treadmill by specifically adapting the step distance of their middle legs. These findings suggest that proprioceptive feedback contributes to leg motor control irrespective of walking speed and that the fly's middle legs play a specialized role in stabilizing locomotion.

Recent advances on the influence of fipronil on insect behavior

Fipronil, a pesticide widely used to control agricultural and household insect pests, blocks insect GABAA and glutamate (GluCl) ionotropic receptors, resulting in uncontrolled hyperexcitation and paralysis that eventually leads to death. The use of fipronil is controversial because unintentional exposure to this compound may contribute to the ongoing global decline of insect pollinator populations. Although the sublethal effects of fipronil have been linked to aberrant behavior and impaired olfactory learning in insects, the precise mechanisms involved in these responses remain unclear. In this article, we highlight recent studies that have investigated the interaction among different pathways involved in the ability of fipronil to modulate insect behavior, with particular emphasis on the role of GABAergic neurotransmission in fine-tuning the integration of sensorial responses and insect behavior. Recent findings suggest that fipronil can also cause functional alterations that affect synaptic organization and the availability of metal ions in the brain.

Comparative connectomics of the descending and ascending neurons of the Drosophila nervous system: stereotypy and sexual dimorphism

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and information bottleneck connecting the brain and the ventral nerve cord (VNC, spinal cord analogue) and comprises diverse populations of descending (DN), ascending (AN) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Integrating three separate EM datasets, we now provide a complete connectomic description of the ascending and descending neurons of the female nervous system of Drosophila and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions have been matched across hemispheres, datasets and sexes. Crucially, we have also matched 51% of DN cell types to light level data defining specific driver lines as well as classifying all ascending populations. We use these results to reveal the general architecture, tracts, neuropil innervation and connectivity of neck connective neurons. We observe connected chains of descending and ascending neurons spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analysis of circuits implicated in sex-related behaviours, including female ovipositor extrusion (DNp13), male courtship (DNa12/aSP22) and song production (AN hemilineage 08B). Our work represents the first EM-level circuit analyses spanning the entire central nervous system of an adult animal.

Motor neurons generate pose-targeted movements via proprioceptive sculpting

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

Organization of an ascending circuit that conveys flight motor state in Drosophila

Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca2+ imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.

Neural mechanisms to incorporate visual counterevidence in self-movement estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.

Fine-grained descending control of steering in walking Drosophila

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.

A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

Multilevel visuomotor control of locomotion in Drosophila

Vision is critical for the control of locomotion, but the underlying neural mechanisms by which visuomotor circuits contribute to the movement of the body through space are yet not well understood. Locomotion engages multiple control systems, forming distinct interacting "control levels" driven by the activity of distributed and overlapping circuits. Therefore, a comprehensive understanding of the mechanisms underlying locomotion control requires the consideration of all control levels and their necessary coordination. Due to their small size and the wide availability of experimental tools, Drosophila has become an important model system to study this coordination. Traditionally, insect locomotion has been divided into studying either the biomechanics and local control of limbs, or navigation and course control. However, recent developments in tracking techniques, and physiological and genetic tools in Drosophila have prompted researchers to examine multilevel control coordination in flight and walking.

Long-timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Circuits for self-motion estimation and walking control in Drosophila

The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.

Neural mechanisms to incorporate visual counterevidence in self motion estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.

Organization of an Ascending Circuit that Conveys Flight Motor State

Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.

The self as part of the sensory ecology: how behavior affects sensation from the inside out

Insects exhibit remarkable sensory and motor capabilities to successfully navigate their environment. As insects move, they activate sensory afferents. Hence, insects are inextricably part of their sensory ecology. Insects must correctly attribute self- versus external sources of sensory activation to make adaptive behavioral choices. This is achieved via corollary discharge circuits (CDCs), motor-to-sensory neuronal pathways providing predictive motor signals to sensory networks to coordinate sensory processing within the context of ongoing behavior. While CDCs provide predictive motor signals, their underlying mechanisms of action and functional consequences are diverse. Here, we describe inferred CDCs and identified corollary discharge interneurons (CDIs) in insects, highlighting their anatomical commonalities and our limited understanding of their synaptic integration into the nervous system. By using connectomics information, we demonstrate that the complexity with which identified CDIs integrate into the central nervous system (CNS) can be revealed.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Proprioception gates visual object fixation in flying flies

Visual object tracking in animals as diverse as felines, frogs, and fish supports behaviors including predation, predator avoidance, and landscape navigation. Decades of experimental results show that a rigidly body-fixed tethered fly in a "virtual reality" visual flight simulator steers to follow the motion of a vertical bar, thereby "fixating" it on visual midline. This behavior likely reflects a desire to seek natural features such as plant stalks and has inspired algorithms for visual object tracking predicated on robust responses to bar velocity, particularly near visual midline. Using a modified flight simulator equipped with a magnetic pivot to allow frictionless turns about the yaw axis, we discovered that bar fixation as well as smooth steering responses to bar velocity are attenuated or eliminated in yaw-free conditions. Body-fixed Drosophila melanogaster respond to bar oscillation on a stationary ground with frequency-matched wing kinematics and fixate the bar on midline. Yaw-free flies respond to the same stimulus by ignoring the bar and maintaining their original heading. These differences are driven by proprioceptive signals, rather than visual signals, as artificially "clamping" a bar in the periphery of a yaw-free fly has no effect. When presented with a bar and ground oscillating at different frequencies, a yaw-free fly follows the frequency of the ground only, whereas a body-fixed fly robustly steers at the frequencies of both the bar and ground. Our findings support a model in which proprioceptive feedback promote active damping of high-gain optomotor responses to object motion.

Ascending neurons convey behavioral state to integrative sensory and action selection brain regions

Knowing one's own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.

Locomotor and olfactory responses in dopamine neurons of the Drosophila superior-lateral brain

The Drosophila brain contains about 50 distinct morphological types of dopamine neurons.^1,2,3,4 Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body,^{5,6,7,8,9,10,11,12,13} where they are implicated in learning.^{14,15,16,17,18} By comparison, we know little about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion.¹⁹ This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements^{20,21,22,23,24,25,26,27,28,29,30}; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. In this study, we monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. We found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, we found that the same identifiable dopamine neuron can encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience.

Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

Natural vision is dynamic: as an animal moves, its visual input changes dramatically. How can the visual system reliably extract local features from an input dominated by self-generated signals? In Drosophila, diverse local visual features are represented by a group of projection neurons with distinct tuning properties. Here, we describe a connectome-based volumetric imaging strategy to measure visually evoked neural activity across this population. We show that local visual features are jointly represented across the population, and a shared gain factor improves trial-to-trial coding fidelity. A subset of these neurons, tuned to small objects, is modulated by two independent signals associated with self-movement, a motor-related signal, and a visual motion signal associated with rotation of the animal. These two inputs adjust the sensitivity of these feature detectors across the locomotor cycle, selectively reducing their gain during saccades and restoring it during intersaccadic intervals. This work reveals a strategy for reliable feature detection during locomotion.

Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors

Deciphering how the brain regulates motor circuits to control complex behaviors is an important, long-standing challenge in neuroscience. In the fly, Drosophila melanogaster, this is coordinated by a population of ~ 1100 descending neurons (DNs). Activating only a few DNs is known to be sufficient to drive complex behaviors like walking and grooming. However, what additional role the larger population of DNs plays during natural behaviors remains largely unknown. For example, they may modulate core behavioral commands or comprise parallel pathways that are engaged depending on sensory context. We evaluated these possibilities by recording populations of nearly 100 DNs in individual tethered flies while they generated limb-dependent behaviors, including walking and grooming. We found that the largest fraction of recorded DNs encode walking while fewer are active during head grooming and resting. A large fraction of walk-encoding DNs encode turning and far fewer weakly encode speed. Although odor context does not determine which behavior-encoding DNs are recruited, a few DNs encode odors rather than behaviors. Lastly, we illustrate how one can identify individual neurons from DN population recordings by using their spatial, functional, and morphological properties. These results set the stage for a comprehensive, population-level understanding of how the brain's descending signals regulate complex motor actions.